Sökning: "xgboost"

Visar resultat 1 - 5 av 80 uppsatser innehållade ordet xgboost.

  1. 1. Predicting hotel cancellations using machine learning

    Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

    Författare :Enok Gartvall; Oscar Skånhagen; [2022-02-18]
    Nyckelord :;

    Sammanfattning : Room cancellations is a big challenge for the hotel industry since the number of guest affects the whole operational setup. The purpose of the thesis is to predict hotel cancella-tions using machine learning and analyse which factors have the most influence. LÄS MER

  2. 2. Employee Turnover Prediction - A Comparative Study of Supervised Machine Learning Models

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Suvoj Reddy Kovvuri; Lydia Sri Divya Dommeti; [2022]
    Nyckelord :Machine Learning; Employee Turnover Prediction; Supervised Learn- ing Models; Logistic Regression; Naive Bayes Classifier; Random Forest Classifier; XGBoost;

    Sammanfattning : Background: In every organization, employees are an essential resource. For several reasons, employees are neglected by the organizations, which leads to employee turnover. Employee turnover causes considerable losses to the organization. LÄS MER

  3. 3. Multivariate Time series Forecasting with applied Machine Learning on Electrical signals from High-Voltage Direct Current Equipment - Valve Cooling System

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Carolina Nilsson; [2022]
    Nyckelord :Machine Learning; LSTM; XGBoost; Forecast; HVDC; Valve Cooling System;

    Sammanfattning : In a sustainable society, utilizing intermittent renewable power plants is an important building block for achieving green power production. However, the power production from these sources, e.g. LÄS MER

  4. 4. Credit risk modelling and prediction: Logistic regression versus machine learning boosting algorithms

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Linnéa Machado; David Holmer; [2022]
    Nyckelord :Machine learning; Credit risk; Logistic regression; Decision trees;

    Sammanfattning : The use of machine learning methods in credit risk modelling has been proven to yield good results in terms of increasing the accuracy of the risk score as- signed to customers. In this thesis, the aim is to examine the performance of the machine learning boosting algorithms XGBoost and CatBoost, with logis- tic regression as a benchmark model, in terms of assessing credit risk. LÄS MER

  5. 5. Predicting television advertisement reach with machine learning models

    Master-uppsats, Linköpings universitet/Databas och informationsteknik

    Författare :Joar Måhlén; Alexander Olsson; [2022]
    Nyckelord :Reach; Machine learning; Television advertisement;

    Sammanfattning : Despite the entry of many media services, television remains the most used media service and accounts for the largest advertising spending globally. One of the main metrics for measuring the successfulness of a television advertising campaign is reach, the percentage of the intended target audience that has seen the television advertisement. LÄS MER